Equitable Division of a Path
Neeldhara Misra, Chinmay Sonar, P. R. Vaidyanathan, Rohit Vaish

TL;DR
This paper investigates fair and efficient resource allocation on a path, demonstrating computational hardness for combined fairness and efficiency, and providing polynomial-time algorithms under relaxed conditions or specific valuation structures.
Contribution
It introduces algorithms for connected EQ1 allocations with relaxed efficiency constraints and extends results to various valuation types and fairness notions.
Findings
Achieving EQ1 with efficiency measures is computationally hard for binary additive valuations.
Connected EQ1 allocations can be computed in polynomial time with a given agent order.
Tractability is possible for binary additive valuations with interval structure when efficiency is required.
Abstract
We study fair resource allocation under a connectedness constraint wherein a set of indivisible items are arranged on a path and only connected subsets of items may be allocated to the agents. An allocation is deemed fair if it satisfies equitability up to one good (EQ1), which requires that agents' utilities are approximately equal. We show that achieving EQ1 in conjunction with well-studied measures of economic efficiency (such as Pareto optimality, non-wastefulness, maximum egalitarian or utilitarian welfare) is computationally hard even for binary additive valuations. On the algorithmic side, we show that by relaxing the efficiency requirement, a connected EQ1 allocation can be computed in polynomial time for any given ordering of agents, even for general monotone valuations. Interestingly, the allocation computed by our algorithm has the highest egalitarian welfare among all…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Data Management and Algorithms
